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. 2016 Nov 9;16(1):662.
doi: 10.1186/s12879-016-2002-4.

Role of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in local dengue epidemics in Taiwan

Affiliations

Role of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in local dengue epidemics in Taiwan

Pui-Jen Tsai et al. BMC Infect Dis. .

Abstract

Background: Aedes mosquitoes in Taiwan mainly comprise Aedes albopictus and Ae. aegypti. However, the species contributing to autochthonous dengue spread and the extent at which it occurs remain unclear. Thus, in this study, we spatially analyzed real data to determine spatial features related to local dengue incidence and mosquito density, particularly that of Ae. albopictus and Ae. aegypti.

Methods: We used bivariate Moran's I statistic and geographically weighted regression (GWR) spatial methods to analyze the globally spatial dependence and locally regressed relationship between (1) imported dengue incidences and Breteau indices (BIs) of Ae. albopictus, (2) imported dengue incidences and BI of Ae. aegypti, (3) autochthonous dengue incidences and BI of Ae. albopictus, (4) autochthonous dengue incidences and BI of Ae. aegypti, (5) all dengue incidences and BI of Ae. albopictus, (6) all dengue incidences and BI of Ae. aegypti, (7) BI of Ae. albopictus and human population density, and (8) BI of Ae. aegypti and human population density in 348 townships in Taiwan.

Results: In the GWR models, regression coefficients of spatially regressed relationships between the incidence of autochthonous dengue and vector density of Ae. aegypti were significant and positive in most townships in Taiwan. However, Ae. albopictus had significant but negative regression coefficients in clusters of dengue epidemics. In the global bivariate Moran's index, spatial dependence between the incidence of autochthonous dengue and vector density of Ae. aegypti was significant and exhibited positive correlation in Taiwan (bivariate Moran's index = 0.51). However, Ae. albopictus exhibited positively significant but low correlation (bivariate Moran's index = 0.06). Similar results were observed in the two spatial methods between all dengue incidences and Aedes mosquitoes (Ae. aegypti and Ae. albopictus). The regression coefficients of spatially regressed relationships between imported dengue cases and Aedes mosquitoes (Ae. aegypti and Ae. albopictus) were significant in 348 townships in Taiwan. The results indicated that local Aedes mosquitoes do not contribute to the dengue incidence of imported cases. The density of Ae. aegypti positively correlated with the density of human population. By contrast, the density of Ae. albopictus negatively correlated with the density of human population in the areas of southern Taiwan. The results indicated that Ae. aegypti has more opportunities for human-mosquito contact in dengue endemic areas in southern Taiwan.

Conclusions: Ae. aegypti, but not Ae. albopictus, and human population density in southern Taiwan are closely associated with an increased risk of autochthonous dengue incidence.

Keywords: Aedes mosquitoes; Breteau index; Dengue fever; Geographically weighted regression; Global bivariate Moran’s I.

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Figures

Fig. 1
Fig. 1
Map of townships in the study area throughout the main island of Taiwan and excluded studied areas of Penghu County and Liouciou Township. A total of 348 studied areas consisted of 294 townships on plain regions (blue and red boxes) and 54 aboriginal townships in mountainous regions (green box), except Wutai Township (black box)
Fig. 2
Fig. 2
Maps of dengue fever incidence, Aedes mosquito density, and human population density in 348 townships in Taiwan during 2009–2011. a Breteau index (BI) of Ae. albopictus during 2009–2011. b BI of Ae. aegypti during 2009–2011. c Comparison between Ae. albopictus and Ae. aegypti density. d Incidence rates of all dengue fever (DF) cases during 2009–2011. e Incidence rates of autochthonous DF cases during 2009–2011. f Incidence rates of imported DF cases during 2009–2011. g Human population density during 2009–2011
Fig. 3
Fig. 3
Moran’s I scatter plot calculated using the original variable and spatial lag as the second variable in Taiwan during 2009–2011. a Breteau index (BI) of Ae. albopictus and imported dengue incidence rate. b BI of Ae. aegypti and imported dengue incidence rate. c BI of Ae. albopictus and autochthonous dengue incidence rate. d BI of Ae. aegypti and autochthonous dengue incidence rate. e BI of Ae. albopictus and dengue fever incidence rate. f BI of Ae. aegypti and dengue fever incidence rate. g Human population density and BI of Ae. albopictus. h Human population density and BI of Ae. aegypti
Fig. 4
Fig. 4
Results of the GWR model for Breteau indices of Ae. albopictus (as the explanatory variable) and imported incidence of dengue fever (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. b Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini–Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011
Fig. 5
Fig. 5
Results of the GWR model for Breteau indices of Ae. aegypti (as the explanatory variable) and the imported incidence of dengue fever (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. a Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini-Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011
Fig. 6
Fig. 6
Results of the GWR model for Breteau indices of Ae. albopictus (as the explanatory variable) and autochthonous incidence of dengue fever (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. b Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini–Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011
Fig. 7
Fig. 7
Results of the GWR model for Breteau indices of Ae. aegypti (as the explanatory variable) and autochthonous incidence of dengue fever (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. b Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini–Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011
Fig. 8
Fig. 8
Results of the GWR model for Breteau indices of Ae. albopictus (as the explanatory variable) and dengue fever incidence rates (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. b Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini–Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011
Fig. 9
Fig. 9
Results of the GWR model for Breteau indices of Ae. aegypti (as the explanatory variable) and dengue fever incidence rates (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. b Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini-Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011
Fig. 10
Fig. 10
Results of the GWR model for human population densities (as the explanatory variable) and Breteau indices of Ae. albopictus (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. b Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini-Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011
Fig. 11
Fig. 11
Results of the GWR model for human population densities (as the explanatory variable) and Breteau indices of Ae. aegypti (as the response variable) in 348 townships in Taiwan during 2009–2011. a Local intercepts during 2009–2011. b Local regression coefficients during 2009–2011. c Significant determination of coefficients according to the Benjamini–Hochberg false discovery rate during 2009–2011. d Local residuals during 2009–2011. e Local R2 values during 2009–2011. f Local condition number values during 2009–2011

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